根据预先确定的列名选择列
还有另一个选项可以避免连续重新输入列名：one_of（）。 您可以预先设置列名，然后在select（）语句中通过将它们包装在one_of（）中或使用!!运算符来引用它们。
classification <- c("name", "genus", "vore", "order", "conservation")
msleep %>%
select(!!classification)
## # A tibble: 83 x 5
## name genus vore order conservation
## <chr> <chr> <chr> <chr> <chr>
## 1 Cheetah Acinonyx carni Carnivora lc
## 2 Owl monkey Aotus omni Primates <NA>
## 3 Mountain beaver Aplodontia herbi Rodentia nt
## 4 Greater short-tailed shrew Blarina omni Soricomorpha lc
## 5 Cow Bos herbi Artiodactyla domesticated
## 6 Three-toed sloth Bradypus herbi Pilosa <NA>
## 7 Northern fur seal Callorhinus carni Carnivora vu
## 8 Vesper mouse Calomys <NA> Rodentia <NA>
## 9 Dog Canis carni Carnivora domesticated
## 10 Roe deer Capreolus herbi Artiodactyla lc
## # ... with 73 more rows根据数据类型选择列
select_if函数允许您传递返回逻辑语句的函数。 例如，您可以使用select_if（is.character）选择所有字符串列。 同样，你可以添加is.numeric，is.integer，is.double，is.logical，is.factor。如果你有日期列，你可以加载lubridate包，并使用is.POSIXt或is.Date。
msleep %>%
select_if(is.numeric) %>%
glimpse
## Observations: 83
## Variables: 6
## $ sleep_total <dbl> 12.1, 17.0, 14.4, 14.9, 4.0, 14.4, 8.7, 7.0, 10.1,...
## $ sleep_rem <dbl> NA, 1.8, 2.4, 2.3, 0.7, 2.2, 1.4, NA, 2.9, NA, 0.6...
## $ sleep_cycle <dbl> NA, NA, NA, 0.1333333, 0.6666667, 0.7666667, 0.383...
## $ awake <dbl> 11.9, 7.0, 9.6, 9.1, 20.0, 9.6, 15.3, 17.0, 13.9, ...
## $ brainwt <dbl> NA, 0.01550, NA, 0.00029, 0.42300, NA, NA, NA, 0.0...
## $ bodywt <dbl> 50.000, 0.480, 1.350, 0.019, 600.000, 3.850, 20.49...您也可以选择否定，但在这种情况下，您需要添加波形符以确保仍将函数传递给select_if。 select_all / if / at函数需要将函数作为参数传递。 如果你必须添加任何否定或参数，你必须将你的函数包装在funs（）中，或者在重新创建函数之前添加波形符。
msleep %>%
select_if(~!is.numeric(.)) %>%
glimpse
## Observations: 83
## Variables: 5
## $ name <chr> "Cheetah", "Owl monkey", "Mountain beaver", "Grea...
## $ genus <chr> "Acinonyx", "Aotus", "Aplodontia", "Blarina", "Bo...
## $ vore <chr> "carni", "omni", "herbi", "omni", "herbi", "herbi...
## $ order <chr> "Carnivora", "Primates", "Rodentia", "Soricomorph...
## $ conservation <chr> "lc", NA, "nt", "lc", "domesticated", NA, "vu", N...按逻辑表达式选择列
实际上，select_if允许您根据任何逻辑函数进行选择，而不仅仅基于数据类型。 例如，可以选择平均值大于500的所有列。 为避免错误，您还必须仅选择数字列，您可以提前执行此操作以获得更简单的语法，也可以在同一行中执行。类似地，'mean> 500本身不是一个函数，所以你需要先添加一个代字号，或者将它包装在funs（）`中以将语句转换为函数。
msleep %>%
select_if(is.numeric) %>%
select_if(~mean(., na.rm=TRUE) > 10)或者更简便:
代码语言：javascript复制msleep %>%
select_if(~is.numeric(.) & mean(., na.rm=TRUE) > 10)
## # A tibble: 83 x 3
## sleep_total awake bodywt
## <dbl> <dbl> <dbl>
## 1 12.1 11.9 50.0
## 2 17.0 7.00 0.480
## 3 14.4 9.60 1.35
## 4 14.9 9.10 0.0190
## 5 4.00 20.0 600
## 6 14.4 9.60 3.85
## 7 8.70 15.3 20.5
## 8 7.00 17.0 0.0450
## 9 10.1 13.9 14.0
## 10 3.00 21.0 14.8
## # ... with 73 more rowsselect_if的另一个有用功能是n_distinct（），它计算可以在列中找到的不同值的数量。例如，要返回少于10个不同答案的列，请在select_if语句中传递~n_distinct（。）<10。 鉴于n_distinct（。）<10不是函数，你需要在前面放一个波浪号。
msleep %>%
select_if(~n_distinct(.) < 10)
## # A tibble: 83 x 2
## vore conservation
## <chr> <chr>
## 1 carni lc
## 2 omni <NA>
## 3 herbi nt
## 4 omni lc
## 5 herbi domesticated
## 6 herbi <NA>
## 7 carni vu
## 8 <NA> <NA>
## 9 carni domesticated
## 10 herbi lc
## # ... with 73 more rows对列重新排序
您可以使用select（）函数（见下文）重新排序列。 您选择它们的顺序将决定最终的顺序。
msleep %>%
select(conservation, sleep_total, name) %>%
glimpse
## Observations: 83
## Variables: 3
## $ conservation <chr> "lc", NA, "nt", "lc", "domesticated", NA, "vu", N...
## $ sleep_total <dbl> 12.1, 17.0, 14.4, 14.9, 4.0, 14.4, 8.7, 7.0, 10.1...
## $ name <chr> "Cheetah", "Owl monkey", "Mountain beaver", "Grea...如果你只是想将几列移到前面，你可以在之后使用everything（）这将简便地添加所有剩余的列。
msleep %>%
select(conservation, sleep_total, everything()) %>%
glimpse
## Observations: 83
## Variables: 11
## $ conservation <chr> "lc", NA, "nt", "lc", "domesticated", NA, "vu", N...
## $ sleep_total <dbl> 12.1, 17.0, 14.4, 14.9, 4.0, 14.4, 8.7, 7.0, 10.1...
## $ name <chr> "Cheetah", "Owl monkey", "Mountain beaver", "Grea...
## $ genus <chr> "Acinonyx", "Aotus", "Aplodontia", "Blarina", "Bo...
## $ vore <chr> "carni", "omni", "herbi", "omni", "herbi", "herbi...
## $ order <chr> "Carnivora", "Primates", "Rodentia", "Soricomorph...
## $ sleep_rem <dbl> NA, 1.8, 2.4, 2.3, 0.7, 2.2, 1.4, NA, 2.9, NA, 0....
## $ sleep_cycle <dbl> NA, NA, NA, 0.1333333, 0.6666667, 0.7666667, 0.38...
## $ awake <dbl> 11.9, 7.0, 9.6, 9.1, 20.0, 9.6, 15.3, 17.0, 13.9,...
## $ brainwt <dbl> NA, 0.01550, NA, 0.00029, 0.42300, NA, NA, NA, 0....
## $ bodywt <dbl> 50.000, 0.480, 1.350, 0.019, 600.000, 3.850, 20.4...列名
有时候列名称本身需要进行更改：
重命名列
如果您将使用select（）语句，则可以在select函数中直接重命名。
msleep %>%
select(animal = name, sleep_total, extinction_threat = conservation) %>%
glimpse
## Observations: 83
## Variables: 3
## $ animal <chr> "Cheetah", "Owl monkey", "Mountain beaver", ...
## $ sleep_total <dbl> 12.1, 17.0, 14.4, 14.9, 4.0, 14.4, 8.7, 7.0,...
## $ extinction_threat <chr> "lc", NA, "nt", "lc", "domesticated", NA, "v...如果要保留所有列，因此不能使用select（）语句，可以通过添加rename（）语句来重命名。
msleep %>%
rename(animal = name, extinction_threat = conservation) %>%
glimpse
## Observations: 83
## Variables: 11
## $ animal <chr> "Cheetah", "Owl monkey", "Mountain beaver", ...
## $ genus <chr> "Acinonyx", "Aotus", "Aplodontia", "Blarina"...
## $ vore <chr> "carni", "omni", "herbi", "omni", "herbi", "...
## $ order <chr> "Carnivora", "Primates", "Rodentia", "Sorico...
## $ extinction_threat <chr> "lc", NA, "nt", "lc", "domesticated", NA, "v...
## $ sleep_total <dbl> 12.1, 17.0, 14.4, 14.9, 4.0, 14.4, 8.7, 7.0,...
## $ sleep_rem <dbl> NA, 1.8, 2.4, 2.3, 0.7, 2.2, 1.4, NA, 2.9, N...
## $ sleep_cycle <dbl> NA, NA, NA, 0.1333333, 0.6666667, 0.7666667,...
## $ awake <dbl> 11.9, 7.0, 9.6, 9.1, 20.0, 9.6, 15.3, 17.0, ...
## $ brainwt <dbl> NA, 0.01550, NA, 0.00029, 0.42300, NA, NA, N...
## $ bodywt <dbl> 50.000, 0.480, 1.350, 0.019, 600.000, 3.850,...格式化所有列名
select_all（）函数允许更改所有列，并将函数作为参数。如果想以大写形式获取所有列名，可以使用toupper（），同样可以使用小写tolower（）。
msleep %>%
select_all(toupper)
## # A tibble: 83 x 11
## NAME GENUS VORE ORDER CONSERVATION SLEEP_TOTAL SLEEP_REM SLEEP_CYCLE
## <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 Cheet~ Acin~ carni Carn~ lc 12.1 NA NA
## 2 Owl m~ Aotus omni Prim~ <NA> 17.0 1.80 NA
## 3 Mount~ Aplo~ herbi Rode~ nt 14.4 2.40 NA
## 4 Great~ Blar~ omni Sori~ lc 14.9 2.30 0.133
## 5 Cow Bos herbi Arti~ domesticated 4.00 0.700 0.667
## 6 Three~ Brad~ herbi Pilo~ <NA> 14.4 2.20 0.767
## 7 North~ Call~ carni Carn~ vu 8.70 1.40 0.383
## 8 Vespe~ Calo~ <NA> Rode~ <NA> 7.00 NA NA
## 9 Dog Canis carni Carn~ domesticated 10.1 2.90 0.333
## 10 Roe d~ Capr~ herbi Arti~ lc 3.00 NA NA
## # ... with 73 more rows, and 3 more variables: AWAKE <dbl>, BRAINWT <dbl>,
## # BODYWT <dbl>你可以通过动态创建函数来进一步：如果你有来自excel杂乱的列名，你可以用下划线替换所有的空格。
代码语言：javascript复制#making an unclean database:
msleep2 <- select(msleep, name, sleep_total, brainwt)
colnames(msleep2) <- c("name", "sleep total", "brain weight")
msleep2 %>%
select_all(~str_replace(., " ", "_"))
## # A tibble: 83 x 3
## name sleep_total brain_weight
## <chr> <dbl> <dbl>
## 1 Cheetah 12.1 NA
## 2 Owl monkey 17.0 0.0155
## 3 Mountain beaver 14.4 NA
## 4 Greater short-tailed shrew 14.9 0.000290
## 5 Cow 4.00 0.423
## 6 Three-toed sloth 14.4 NA
## 7 Northern fur seal 8.70 NA
## 8 Vesper mouse 7.00 NA
## 9 Dog 10.1 0.0700
## 10 Roe deer 3.00 0.0982
## # ... with 73 more rows或者，如果您的列包含其他数据，例如问题编号：
代码语言：javascript复制#making an unclean database:
msleep2 <- select(msleep, name, sleep_total, brainwt)
colnames(msleep2) <- c("Q1 name", "Q2 sleep total", "Q3 brain weight")
msleep2[1:3,]
## # A tibble: 3 x 3
## `Q1 name` `Q2 sleep total` `Q3 brain weight`
## <chr> <dbl> <dbl>
## 1 Cheetah 12.1 NA
## 2 Owl monkey 17.0 0.0155
## 3 Mountain beaver 14.4 NA您可以将select_all与str_replace结合使用以消除额外的字符。
msleep2 %>%
select_all(~str_replace(., "Q[0-9] ", "")) %>%
select_all(~str_replace(., " ", "_"))
## # A tibble: 83 x 3
## `_name` `_sleep total` `_brain weight`
## <chr> <dbl> <dbl>
## 1 Cheetah 12.1 NA
## 2 Owl monkey 17.0 0.0155
## 3 Mountain beaver 14.4 NA
## 4 Greater short-tailed shrew 14.9 0.000290
## 5 Cow 4.00 0.423
## 6 Three-toed sloth 14.4 NA
## 7 Northern fur seal 8.70 NA
## 8 Vesper mouse 7.00 NA
## 9 Dog 10.1 0.0700
## 10 Roe deer 3.00 0.0982
## # ... with 73 more rows行名转换成列
某些数据框的行名本身有意义，例如mtcars数据集：
代码语言：javascript复制 mtcars %>%
head
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1如果希望此列成为实际列，则可以使用rownames_to_column（）函数，并指定新列名。
mtcars %>%
tibble::rownames_to_column("car_model") %>%
head
## car_model mpg cyl disp hp drat wt qsec vs am gear carb
## 1 Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## 2 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## 3 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## 4 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## 5 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## 6 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
